Edward Conard

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  • “Unintended Consequences provides a provocative interpretation of the causes of the global financial crisis and the policies needed to return to rapid growth. Whether you agree or not, this analysis is well worth reading.” - Nouriel Roubini, New York University; Chairman, Roubini Global Economics
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Why the U.S. Economy Is Trouncing Europe’s

Edward Conard Wall Street Journal
Date Posted:
December 17, 2024
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My WSJ OpEd argues that mining the technological frontier motivates America’s talent to take more risk by increasing expected after-tax payoffs, producing a 70X difference in the value of newly created companies—laughably missed by tax elasticity studies.

My WSJ OpEd argues that mining the technological frontier motivates America’s talent to take more risk by increasing...
Economists never cite one of the most significant statistics about the U.S. economy. According to data released last week by the Organization for Economic Cooperation and Development, only about 12% of Americans score at the highest levels on internationally administered academic tests, while 34% score at the lowest levels—nearly three low scorers for every high scorer. Germany’s figures are nearly even: 18% score at the highest levels and 20% at the lowest. Put another way, Germany’s ratio of high to low scorers is almost three times America’s. Scandinavia’s is five times; Japan’s, seven.

These enormous differences have profound economic implications. With more talent and fewer needy people, is it any wonder that Northern European countries can afford more-generous welfare policies than their neighbors to the south?

Yet America excels relative to Europe despite these enormous differences. While Europe has created 14 companies worth more than $10 billion in the past 50 years, with about $400 billion of market value in total, Americans have created nearly 250 such companies, worth $30 trillion.

That success has driven up America’s middle-class incomes. The median disposable U.S. household income, according to the OECD, is now 25% greater than the median German household and 60% greater than the median household in Italy.

Europeans’ incomes would be even lower if they weren’t free-riding on American innovation, defense spending and higher drug prices, which incentivize research. America’s median incomes would be higher if we had more talent devoted to supervising and creating jobs for blue-collar workers or Northern Europe-like distribution of test scores.

The outsize success of America’s talented entrepreneurs doesn’t stem from their superior intelligence. It comes from working at companies such as Google and Microsoft, which mine the technological frontier and expose employees to valuable knowledge, insights and opportunities. Apple is worth more than the 30 largest German companies combined. Apple’s employees and its alumni use their knowledge and training to create more value than their counterparts in Europe.

Unlike Europe, the enormous success of American entrepreneurs motivated an army of talented Americans to get valuable on-the-job training, work longer hours, take risks and succeed. A small amount of success bubbles up from a large pool of failure.

The belief that taxing success more heavily will scarcely slow inevitable progress ignores the importance of being first to market and founding successful companies in America rather than the rest of the world, the enormous difference in the training and expected payoffs for successful risk-taking that it creates for America’s talented workers, and the motivational effect higher expected payoffs for successful risk-taking have on our talented workers.

Studies of short-term tax elasticity laughably miss the enormous difference between the success of the U.S. and Europe. Even if Europe cut its tax rates, it would have a trivial short-term effect on the expected returns to risk-taking, because without companies such as Google, entrepreneurs wouldn’t come up with ideas worthy of investment regardless of the tax rate. It takes decades of successful risk-taking to create companies and workers who can spawn the next generation of success.

The argument that we can heavily tax the tail of the distribution of payoffs without discouraging prudent risk-taking—since entrepreneurs such as Bill Gates and Steve Jobs took risks without expecting the enormous success they achieved—fails to recognize that outsize payoffs at the tail of the distribution critically drive overall expected risk-adjusted returns above break-even. Even with these successes, the returns to venture capital over the last 20 years have been mediocre at best.

When entrepreneurs capture as little as 5% of the value they create for others, it makes little sense to encourage successful risk-takers to quit working long before they achieve outsize success. With the effect technological success has on the productivity of talented American workers, who are our constraint to growth, and the effect of their productivity on the growth of middle-class incomes relative to Europe, that’s not a “policy failure.”

The fastest way to accelerate America’s growth and increase tax revenues is to let high-skilled immigration expand our talent pool. Forty percent of America’s billion-dollar startups were founded by high-skilled immigrants—roughly the same percentage of STEM doctorates held by foreign-born American workers.

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More Macro Roundup Articles related to Ed's Wall Street Journal Op-ed "Trouncing Europe" (24 articles)

A Visualization of Europe's Non-Bubbly Economy

Andrew McAfee The Geek Way
Date Posted:
December 3, 2024
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There are only 13 EU-based firms less than 50 years old with a market cap of > $10B, with a combined market cap of $400B. The comparable US cohort is worth $30T, 70x that of its EU equivalent. @amcafee

Of all the [hard-hitting statistics] in the Draghi report, though, the ones that most startled me were in this sentence: “there is no EU company with a market capitalisation over EUR 100 billion that has been set up from scratch in the last fifty years, while all six US companies with a valuation above EUR 1 trillion have been created in this period.” How many arriviste European companies are worth at least $10B (I’m switching from euros to dollars here)? We found 13 EU arrivistes worth at least $10B. The total market cap of this continental treize is about $400B. The US has a large and variegated population of valuable young from-scratch companies. The EU simply doesn’t. The American population of arrivistes worth at least $10B is collectively worth almost $30 trillion dollars — more than 70 times as much as its EU equivalent.

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  • Draghi is Trying To Save Europe From Itself — .@martinwolf_ notes that Europe has fallen behind the US in technological innovation: in the last 50 years, no new EU-based company has achieved a market cap…
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The Future of European Competitiveness – A Competitiveness Strategy for Europe

Mario Draghi and Staff European Commission
Date Posted:
September 18, 2024
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An EC study of European competitiveness finds that EU gross value-added per hour worked increased by 0.7%/year from 2000-19, vs. 1.2%/year in the US. “Europe is lagging in the breakthrough digital technologies that will drive growth in the future.”

The EU’s aggregate gap in labour productivity growth compared with the US reflects differences in industry composition, sectoral innovation, and technology diffusion. The EU economy has traditionally been strong in all mid-technology sectors that are not at the centre of radical technological advances, but [has seen] less activity in sectors in which much of the productivity growth has originated in recent years, notably the ICT sector and the exploitation of large-scale digital services. Excluding the main ICT sectors (the manufacturing of computers and electronics and information and communication activities) from the analysis, EU productivity has been broadly at par with the US in the period 2000-2019. To digitalise and decarbonise the economy and increase our defence capacity, the investment share in Europe will have to rise by around 5 percentage points of GDP to levels last seen in the 1960s and 70s. This is unprecedented: for comparison, the additional investments provided by the Marshall Plan between 1948-51 amounted to around 1-2% of GDP annually.

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The US Borrowing Surge: Outpacing Europe for the Foreseeable Future

Jesper Rangvid Rangvid's Blog
Date Posted:
December 16, 2024

By 2034, Euro area government debt is projected to reach 100% of GDP, up 11pp from 2024. Under the CBO baseline, which excludes Trump’s campaign proposals, US government debt is projected to reach 122% of GDP by 2034, up 25pp.

Over the next decade, the debt-to-GDP ratio in the euro area is projected to rise by 11 percentage points, reaching 100% of GDP by 2034. While this represents a significant level of debt, the situation in the US is even more concerning. Public debt in the US is expected to increase by twice as much—by 25 percentage points—over the same period, reaching 122% of GDP by 2034. While borrowing and spending can stimulate economic activity in the short term, the money must eventually be repaid. The US economy enjoys significant structural advantages over Europe, including less burdensome regulation, a more favourable demographic outlook, greater innovation, and more. However, if the US fails to address its mounting debt, it risks severe long-term consequences.

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Do Adults Have the Skills They Need to Thrive in a Changing World?

OECD Staff Organisation for Economic Co-operation and Development
Date Posted:
December 10, 2024
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The 2023 OECD Survey of Adult Skills reveals the US has ~ 3 low-scorers for every high-scorer. Germany has nearly 3X as many high-scorers per low-scorer as the US; Scandinavia has more than 5X and Japan more than 7X.

Adults at Level 5 can use and apply problem-solving strategies to analyse, evaluate, reason, and critically reflect on complex and formal mathematical information, including dynamic representations. They demonstrate an understanding of statistical concepts and can critically reflect on whether a data set can be used to support or refute a claim. Adults at Level 1 can interpret simple spatial representations or a scale on a map. Identify and extract information from a table or graphical representation or complete a simple whole number bar chart. Identify the largest value in an unordered list, including comparing the decimal part of the number, and interpret and perform basic arithmetic operations, including multiplication and division, with whole numbers, money, and common whole-number percentages, such as 25% and 50%. Adults performing Below Level 1 can count up to 20 objects that are displayed with varying degrees of organisation, sort events by chronological order, compare unordered lists of numbers to identify the largest number based on the whole-number component, locate data directly from a graph, and perform addition and subtraction with small whole numbers.

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Euro Bashing Abounds, But Remember That US Growth is Debt-Fuelled

Rangvid's Blog Jesper Rangvid
Date Posted:
December 9, 2024
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Taking a demand side view, Jesper Rangvid argues that if US debt/GDP had increased by Europe’s 21pp instead of 60pp since 2007, with a conservative multiplier of 0.3 US GDP growth would have exceeded Europe’s by only 5pp vs. 23pp.

Since 2007, government debt as a share of GDP has risen by 21 percentage points in the euro area but three times as much—60 percentage points—in the US. This much larger debt expansion has significantly bolstered US economic activity. The extent of this impact depends on the ‘fiscal multiplier’—the additional economic activity generated by each dollar of government spending. Assuming a fiscal multiplier of 0.3 (where one dollar of government spending adds 0.3 dollars of economic activity), the US economy would have grown only 5 percentage points more than the euro area between 2007 and 2023 when adjusting for US debt-fuelled growth. This contrasts sharply with the observed growth difference of 23 percentage points (fiscal multiplier of 0 in the figure). In other words, a substantial portion of the US growth advantage since the financial crisis has been driven by debt-financed fiscal policy expansions, making Europe’s relative growth performance appear less unfavourable. Debt-fuelled growth is not sustainable.

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Cost of Failure and Competitiveness In Disruptive Innovation

Yann Coatanlem and Oliver Coste Universita Bocconi
Date Posted:
December 6, 2024

.@YannCoatanlem and @olivercoste find that restructuring costs in the EU are 10x that of the US and argue that “the cost of failure is a first-order factor of Europe’s lag in tech, with major consequences for its competitiveness and standard of living.”

We find that the profitability of high-risk tech companies, associated with high rates of failure, is very dependent on the cost of restructuring, which itself is driven by employment protection legislation. Leveraging a combination of financial analysis, empirical observations, and limited existing literature, we estimate that restructuring costs (that include much more than severance packages) are approximately 10 times higher in countries with high labor protection, such as in Western Europe, than in countries with low labor protection such as in the United States. We show that this cost differential translates into lower returns on capital in tech industries and confirm that impact empirically. We explain that the cost of failure is a first order factor of Europe’s lag in tech, with major consequences for its competitiveness, its standard of living and its security. A key insight is that restructuring costs matter even if they apply only to larger enterprises because the high return from the few winners materializes only once they become larger.

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  • The Future of European Competitiveness – A Competitiveness Strategy for Europe — An EC study of European competitiveness finds that EU gross value-added per hour worked increased by 0.7%/year from 2000-19, vs. 1.2%/year in the US. “Europe…
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The American Economy Has Left Other Rich Countries In The Dust

Simon Rabinovitch and Henry Curr The Economist
Date Posted:
October 15, 2024
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Between 1990 and today, the US share of G7 GDP increased from 40% to ~ 50%. Mean wages in Mississippi, the poorest state in the US, are higher than mean wages in the UK, Canada, and Germany. @S_Rabinovitch @currhenry

In 1990 America accounted for about two-fifths of the overall GDP of the G7 group of advanced countries; today it is up to about half On a per-person basis, American economic output is now about 40% higher than in Western Europe and Canada, and 60% higher than in Japan—roughly twice as large as the gaps between them in 1990. Average wages in America’s poorest state, Mississippi, are higher than the averages in Britain, Canada, and Germany. America’s outperformance has accelerated recently. Since the start of 2020, just before the covid-19 pandemic, America’s real growth has been 10%, three times the average for the rest of the G7 countries. Among the G20 group, which includes large emerging markets, America is the only one whose output and employment are above pre-pandemic expectations, according to the International Monetary Fund.

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Which U.S. Stocks Generated the Highest Long-Term Returns?

Hendrik Bessembinder Arizona State University
Date Posted:
July 25, 2024
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Hendrik Bessembinder finds that from 1925 to 2023 51.6% of equities had a negative return; however, 17 stocks had cumulative returns greater than $50,000 per dollar invested, led by Altria Group with a return of $2.65mm for each dollar invested.

This report describes compound return outcomes for the 29,078 publicly-listed common stocks contained in the CRSP database from December 1925 to December 2023. The majority (51.6%) of these stocks had negative cumulative returns. However, the investment performance of some stocks was remarkable. Seventeen stocks delivered cumulative returns greater than five million percent (or $50,000 per dollar initially invested), with the highest cumulative return of 265 million percent (or $2.65 million per dollar initially invested) accruing to long-term investors in Altria Group. Annualized compound returns to these top performers relatively were modest, averaging 13.47% across the top seventeen stocks, thereby affirming the importance of “time in the market.” The highest annualized compound return for any stock with at least 20 years of return data was 33.38%, earned by Nvidia shareholders.

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Can Europe’s Economy Ever Hope To Rival the US Again?

Martin Arnold, Sam Fleming and Claire Jones Financial Times
Date Posted:
May 13, 2024
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Erik Nielsen, economics adviser at Italian bank UniCredit, says investment in the US has increased more than 8% since the end of 2019 and is still growing strongly at the start of 2024, while the Eurozone remained 4% below pre-Covid levels.

The biggest publicly traded European companies with more than a billion dollars of annual revenue, including those in the UK, Norway, and Switzerland, invested $400bn less than their US counterparts in 2022. Volkswagen was the only EU company that appeared in the top 10 in a recent European Commission report examining the world’s top 2,500 R&D investors in 2023. Six of the top 10 were headquartered in the US and none were in the UK. The R&D spending of the so-called Magnificent Seven companies amounted to more than $200B last year, around half of Europe’s total equivalent spending across all private and public sectors. The mismatch in venture capital funding is stark. Last year VC investment in US companies was almost treble what those in Europe managed, according to KPMG research. VC funds in the US also raised almost five times as much as those in Europe over the past three years.

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Europeans ‘Less Hard-Working’ Than Americans, Says Norway Oil Fund Boss

Richard Milne and Robin Wigglesworth Financial Times
Date Posted:
April 25, 2024
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The CEO of Norway’s $1.6T oil fund notes that US companies have outpaced their European rivals in innovation and technology; “There’s a mindset issue in terms of acceptance of mistakes and risks…the Americans just work harder.”

The CEO of Norway’s $1.6T oil fund notes that US companies have outpaced their European rivals in innovation and...
Nicolai Tangen noted it's “worrisome” that American companies were outpacing their European rivals on innovation and technology, leading to vast outperformance of US shares in the past decade. “There’s a mindset issue in terms of acceptance of mistakes and risks. You go bust in America, you get another chance. In Europe, you’re dead,” he said, adding that there was also a difference in “the general level of ambition. We are not very ambitious. I should be careful about talking about work-life balance, but the Americans just work harder.” Its US holdings have increased in the past decade while its European ones have declined. US shares account for almost half of all its equities compared with 32% in 2013. The leading European country — the UK — represented 15% of its equity portfolio a decade ago but just 6% last year. The fund is invested in about 9,000 companies worldwide, but seven US technology companies — Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla — account for about 12% of its equity portfolio.

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Taxing Top Wealth: Migration Responses and Their Aggregate Economic Implications

Katrine Jakobsen, Henrik Kleven, Jonas Kolsrud, Camille Landais and Mathilde Muñoz National Bureau of Economic Research
Date Posted:
February 21, 2024
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In Sweden and Denmark, a 1pp increase in the mean wealth tax reduced the stock of rich taxpayers by 2%. When an entrepreneur subject to the wealth tax emigrates, employment in their businesses drops by 33%, and tax payments by 50%. @MathildeMunoz

We show that, when an entrepreneur subject to the wealth tax out-migrates, employment in their businesses drops by 33%, value-added by 34%, tax payments by 50%, and gross investments by 21%. Our data enable us to delve beyond firm-level effects and explore the reallocation of economic activity within Sweden following the out-migration of wealthy entrepreneurs. We find substantial reallocation: 60% of the firms closed by their wealthy owners upon out-migration end up being absorbed by other companies in Sweden, and employees at these firms experience limited persistent losses in labor earnings or employment prospects. Overall, our results indicate that the impact of wealthy entrepreneur expatriation on aggregate domestic activity is mitigated by reallocation forces in the Swedish labor market. We show that wealthy out-migration is associated with tax revenue losses from wealth, income, and local taxes. We also find evidence of negative spillovers of out-migration through reduced employment, investments, and tax payments at firms held by wealthy entrepreneurs. A 1pp increase in the effective average tax rate on wealth increases net out-migration by .22pp (+0.17 pp for out-migration and -.05 pp for in-migration). Our results indicate that these aggregate effects are small. A 1pp decrease in the effective average tax rate on wealth increases the size of the wealthy population by at most 2% in the long run, with an induced impact on aggregate employment and total investment in the economy of .03% and .04%, respectively.

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Europe Regulates Its Way to Last Place

Greg Ip Wall Street Journal
Date Posted:
February 2, 2024

European firms with at least $1B in revenue spent 3.7% of revenue on R&D vs. 6.8% for comparable US firms, and earned 14% ROIC vs. 17.8% for US firms. @greg_ip points to European competition policy as a driver.

Europe’s economy underperforms for lots of reasons, from demographics to energy costs, not just regulation. And U.S. regulators aren’t exactly hands-off. Still, they tend to act on evidence of harm, whereas Europe’s will act on the mere possibility. This precautionary principle can throttle innovation in its cradle. The McKinsey Global Institute noted Europe’s internal market is larger than China’s and almost as big as the U.S.’s. But when it compared companies with more than $1 billion in revenue, the U.S. firms spent 80% more on research and development, boasted 30% higher return on capital, and 1.3-percentage points faster revenue growth.

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  • Erik Brynjolfsson: ‘This Could Be The Best Decade in History — Or The Worst’ — .@erikbryn argues that generative AI will drive annual productivity growth over twice the CBO’s 1.4% forecast in the 2020s, citing recent research…
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Increasing Returns: Identifying Forms of Increasing Returns and What Drives Them

Michael Mauboussin and Dan Callahan Morgan Stanley
Date Posted:
January 31, 2024

Increasing returns on capital may be driven by superstar firms that outspend their competitors on R&D and better management practices which they can then scale. @mjmauboussin

The gap in productivity between the best and worst companies within industries is large. For instance, economists measured the productivity of U.S. manufacturing plants and found that the output at the 90th percentile was nearly double that of those at the 10th percentile. Economists do not fully understand why that difference is so large, but they commonly attribute it to management talent. Organizations do not always identify and implement best practices. Superstar firms substantially outspend their competitors on intangible assets. They are spending big on “ideas”: software, training, and research and development (R&D). James Bessen documents that spending for proprietary software has grown substantially faster than that for R&D, acquisitions, advertising, and lobbying. U.S. firms spend more than $200 billion per year on proprietary software and the big firms represent the bulk of that outlay. They are investing heavily in nonrival goods. Bessen then makes the case that proprietary software enables superstar firms to capture classic economies of scale and to offer differentiated products.

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  • The Economics of Inequality in High-Wage Economies — French workers who joined the technology sector from 1994-2002 earned 6% lower wages 15 years out relative to similar workers starting in other sectors…
  • Long-Term Shareholder Returns: Evidence From 64,000 Global Stocks — Hendrik Bessembinder finds that the best-performing 1,526 global firms (2.4% of total) accounted for all of the $75.7T in net global stock market wealth…
  • Birth, Death, and Wealth Creation — As firms have stayed private longer wealth creation has shifted from public to private markets. @mjmauboussin
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  • GDP
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FDI and Superstar Spillovers: Evidence from Firm-to-Firm Transactions

Mary Amiti, Cédric Duprez, Jozef Konings and John Van Reenen National Bureau of Economic Research
Date Posted:
October 12, 2023
Is Database:
Database

Evidence from Belgian btw 2002-14 suggests that large firms generate significant TFP spillovers to domestic suppliers. Firms that start a serious relationship with a superstar firm increase their TFP by 8% three or more years after the relationship is formed.

We use an event study approach, examining what happens when a firm begins supplying a foreign multinational for the first time. We uncover a sharp increase in productivity (which rises by about 8% after three years) and other performance measures (e.g. sales to firms other than the new multinational partner). The fraction of aggregate value accounted for by multinationals declined by about ten percentage points in Belgium in our sample period (2002 and 2014), which would suggest a strong headwind against productivity growth. However, in a novel result we are also able to document that when we look at similar events of starting a serious relationship with other “superstar firms” - defined as those who are in the top thousandth of the size distribution and/or export intensively - we find very similar performance impacts.

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  • Mega Firms and Recent Trends in the U.S. Innovation: Empirical Evidence from the U.S. Patent Data — .@_seulakim documents the importance of the 50 largest US firms in generating novel patents that combine technical components in new ways.
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On Getting Older

Euro Intelligence Staff Euro Intelligence
Date Posted:
September 28, 2023

The 5 largest American firms were all founded within the last 50 years, vs. only one firm in the German Dax 30. Euro Intelligence staff argues that this is driven by government policies.

Europeans are using our high taxes to fund social transfers, not public sector investments. Innovators are therefore confronted with the worst of all worlds: a capital market not fit for purpose, high taxes, and low public sector investments. For a capital-markets driven system of innovation, you require a complete reboot of your entire socio-economic system. You would need to replace your pay-as-you go pension systems with pension funds. You would have to stop subsidising old industries and let them fall over the cliff. You would need lower rates of corporate taxes, which you can only have through cuts in social transfers. You would also need to raise public investment spending. It is safe to predict that this will not happen, not even during a long-lasting period of economic decline. We know the politics of decline.

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  • Growth
  • GDP
  • Politics

Long-Term Shareholder Returns: Evidence From 64,000 Global Stocks

Hendrik Bessembinder, Te-Feng Chen, Goeun Choi and K.C. John Wei Financial Analysts Journal
Date Posted:
September 11, 2023
Is Database:
Database
Is Important:
Important

Hendrik Bessembinder finds that the best-performing 1,526 global firms (2.4% of total) accounted for all of the $75.7T in net global stock market wealth creation between 1990 and 2020.

We calculate net global stock market wealth creation of $US 75.7 trillion btw 1990 and 2020. Wealth creation is highly concentrated. Five firms (0.008% of the total) with the largest wealth creation during the January 1990 to December 2020 period (Apple, Microsoft, Amazon, Alphabet, and Tencent) accounted for 10.3% of global net wealth creation. The best-performing 159 firms (0.25% of total) accounted for half of global net wealth creation. The best-performing 1,526 firms (2.39% of the total) can account for all net global wealth creation. Skewness in compound returns is even stronger outside the U.S. The present sample includes 46,723 non-U.S. stocks. Of these, 42.6% generated buy-and-hold returns measured in U.S. dollars that exceed one-month U.S. Treasury bill returns over matched horizons. By comparison, 44.8% of the 17,776 U.S. stocks in the present sample outperformed Treasury bills.

Related Articles:

  • Birth, Death, and Wealth Creation — As firms have stayed private longer wealth creation has shifted from public to private markets. @mjmauboussin
  • More Bang for Your Buck — Capital inflows into North American markets have contributed to a 3.9x Price/Book value relative to market averages of 1.9x in Europe and 1.4x in Japan…
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  • Financial Markets
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  • Growth
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From Strength To Strength

Economist Staff The Economist
Date Posted:
April 13, 2023

Growth in the US has outpaced growth in other advanced peer economies. In 1990, the US accounted for 40% of the nominal GDP of the G7, today it accounts for 58%. @TheEconomist

America’s $25.5trn in GDP last year represented 25% of the world’s total—almost the same share as it had in 1990. On that measure China’s share is now 18%. In 1990 America accounted for 40% of the nominal GDP of the G7, a group of the world’s seven biggest advanced economies, including Japan and Germany. Today it accounts for 58%. In PPP terms the increase was smaller, but still significant: from 43% of the G7‘s GDP in 1990 to 51% now. America’s outperformance has translated into wealth for its people. Income per person in America was 24% higher than in western Europe in 1990 in PPP terms; today it is about 30% higher. It was 17% higher than in Japan in 1990; today it is 54% higher. America’s labour-force participation rate has been falling this century, largely because of men dropping out of the workforce. But this American oddity is not large enough to make up for the country’s advantage in raw numbers. Even with lower participation, the past three decades have seen America’s labour force grow by 30%. In Europe the number is 13%, in Japan, just 7%. America’s working-age population—those between 25 and 64—rose from 127m in 1990 to 175m in 2022, an increase of 38%. Contrast that with western Europe, where the working-age population rose just 9% during that period, from 94m to 102m.
  • Growth
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Why Is Europe More Equal Than The United States

Thomas Blanchet, Lucas Chancel and Amory Gethin Paris School Of Economics
Date Posted:
June 7, 2022
Is Database:
Database
Is Important:
Important

The US redistributes a larger fraction of its national income to the poorest 50% than any European country, with the bottom 50% receiving a net transfer of 6% of national income in 2017.

Despite the common perception that Europe is more redistributive, the US redistributes a larger fraction of its national income to the poorest 50% than any European country. In 2017, the bottom 50% in the US received a net transfer of 6% of national income, compared to about 4% in Western and Northern Europe and less than 3% in Eastern Europe. This is partly due to the US tax-and-transfer system being more progressive, with the top 10% seeing their income decrease by 8% after taxes and transfers, compared to about 4% in Western and Northern Europe. However, Europe taxes and redistributes a larger share of its national income overall (47% vs. 35% in the US), with higher indirect taxes that disproportionately affect low-income earners. Additionally, Europe's more developed public pension systems contribute to higher redistribution estimates when pensions are included in analyses.

Thomas Blanchet, Lucas Chancel and Amory Gethin, "Why Is Europe More Equal Than The United States,"Paris School Of Economics, November 9, 2021, https://wid.world/document/why-is-europe-more-equal-than-the-united-states-world-inequality-lab-wp-2020-19/

“…Why do our conclusions contradict the standard view on redistribution in Europe and the US? We find that this is the case for three main reasons. First, OECD estimates rely exclusively on surveys, while we systematically distribute the entire national income by combining surveys with tax data and national accounts. Second, standard estimates of redistribution only allocate direct taxes and transfers to individuals, thereby ignoring corporate taxes, indirect taxes, and in-kind transfers. Distributing these components of government revenue and expenditure reverts the rankings of Europe and the US in terms of redistribution. This is because indirect taxes are much higher in Europe than in the US and fall disproportionately on low-income earners. Third, our benchmark measure of redistribution compares pretax incomes to Post tax incomes, while the standard view tends to compare factor incomes (sometimes referred to as market incomes) to posttax incomes. Because many European countries have a greater share of pensioners than the United States, and because public pension systems are much more developed in Europe than in the US, including pensions in the analysis leads to increasing estimates of redistribution more in the former than in the latter. However, as we now show, our conclusions are strongly robust to using one or the other of these two income concepts….”

Predistribution vs. Redistribution: Revisiting the Europe-US inequality gap

“…Figure VIIa directly answers this question by representing the share of national income transferred by the tax-and-transfer system between pretax income groups in Eastern Europe, Western and Northern Europe, and the United States in 2017. The bottom 50% and the middle 40% are net beneficiaries of redistribution in all three regions, but the US tax-and-transfer system appears to be unequivocally more progressive. The bottom 50% in the US received a positive net transfer of 6% of national income in 2017, compared to about 4% inWestern and Northern Europe and less than 3% in Eastern Europe. Meanwhile, the top 10% saw their average income decrease by 8% of national income in the US after taxes and transfers, compared to about 4% in Western and Northern Europe and 3% in Eastern Europe. The middle 40% benefits slightly more from redistribution in the US (2%) than in Europe (less than 1%)….”

The Net Impact of Taxes and Transfers on Inequality

“…FigureVIbprovides a complementary picture of the magnitude and progressivity of government expenditure by plotting total transfers received by the bottom 50% in European countries and the United States, expressed as a share of national income. The US ranks third in terms of the smallest share of national income transferred to the bottom 50% (about 13%), due mainly to lower expenditure on pensions. In Europe, transfers received by the poorest half of the population are smallest in Serbia (11%), followed by Romania (12%), Estonia (14%), and Poland (14%). Meanwhile, Denmark, the Czech Republic, Sweden, the Netherlands, Belgium, and Finland stand out as the European countries allocating the greatest share of national income to the poorest half of the population (22-23%, corresponding to slightly less than half of all government revenue in these countries)….”

“…As for taxes, total government expenditure is significantly lower in the US (35% of national income) than in Europe (47%).36 The difference between the two regions is due to cash transfers, which represent 9% of national income in the US compared to 23% in Europe. Within cash transfers, pensions are the aggregate that differs the most between the two regions (16% of national income in Europe versus 5% in the US), followed by family and social assistance transfers (5% vs. 3%) and unemployment and disability benefits (1.6% vs. 1.4%). Meanwhile, in-kind transfers in health, education, and other collective government expenditure are very similar in Europe and the US (25-26%, of which about 7% goes to health). Total government expenditure is higher in Northern Europe (51% of national income) and Western Europe (48%) than in Eastern Europe (42%), due mainly to the larger size of social assistance transfers (5% inWestern and Northern Europe vs. 3.5% in Eastern Europe) and in-kind transfers (29% vs. 25% vs. 23%, respectively) in Western and Northern Europe. Figure VIa presents the distribution of transfers across posttax income groups in Europe and the US, expressed as a share of posttax national income. Unsurprisingly, transfers are progressive in both the US and Europe: they represent over 60% of the posttax incomes of bottom deciles, compared to less than 30% of those of the top 1%. Pensions represent a smaller share of posttax income in the US than in Europe for all posttax income groups, while the distribution of other cash transfers is relatively similar between the two regions. Health payments are the most progressive type of transfers. In Europe, this is directly due to the fact that we distribute health expenditure on a lump-sum basis, assuming as a first approximation that all individuals benefit from the same in-kind transfer (see methodology). Health expenditure is also highly progressive in the United States, where public health spending is significant and targeted towards the very poor (via Medicaid). Other in-kind transfers are neither progressive nor regressive, because we assume that they are distributed proportionally to posttax disposable income (we come back to this assumption in the next section)…”

The Structure and Distribution of Transfers

“…By doing so and by narrowing down the analysis to the employed and working-age (20-64) population, the analysis remains consistent and cross-country comparisons meaningful. The main conclusions are unchanged. Because social contributions fall on labor income and are generally set at fixed rates, they tend to be flat for most groups within the bottom 90% and regressive at the top. This turns the tax systems of Western and Northern European countries into approximately flat tax systems, while those of most Eastern European countries become strongly regressive at the top end of the distribution. Because social contributions are smaller in the United States than in Europe, the US tax system remains more progressive than that of all European countries (with the exception of the UK)….”

“…Figure Vb ranks European countries and the United States according to a simple measure of tax progressivity: the ratio of the total tax rate faced by the top 10% to that of the bottom 50%. The composition of bars correspond to the composition of taxes paid by the top 10%. The US stands out as the country with the highest level of tax progressivity: the top decile faces a tax rate that is more than 70% higher than that of the poorest half of the population. By this measure, the European country with the most progressive tax system is the United Kingdom, followed by Norway, the Czech Republic, and France. Many European countries have values close to 1 on this indicator, corresponding to relatively flat tax systems, in which top income groups face a tax rate approximately equal to that of the bottom 50%....”

“..Figure Va represents the level and composition of non-contributory taxes paid by pretax income group in Eastern Europe, Western and Northern Europe, and the United States in the past decade.34 Two results clearly stand out. First, while taxes paid are lower in the US than in Europe for most pretax income groups, the taxation profile is unambiguously more progressive in the United States. The top 1% face a tax rate higher than 30% in the US, which is relatively comparable to what we observe in Western and Northern Europe. Meanwhile, bottom income groups are taxed an average rate that is nearly twice as small in the US as in Europe. Second, the difference in tax progressivity between the two regions is mainly driven by indirect taxes, which represent a significantly larger share of national income in Europe than in the US. These taxes tend to be regressive, because they are paid proportionally to consumption…”

“…Before investigating the distributional impact of taxes, it is useful to briefly compare the size and composition of government revenue in Europe and the United States.33 In 2007-2017, taxes and social contributions amounted to 47% of national income in Europe, compared to 28% in the United States. The United States collected less tax revenue than any European country, from Romania (32%), the country with lowest tax revenue, to Denmark (57%), which displayed the highest tax to national income ratio. The gap between the two regions was driven by two components of revenue: social contributions, which represented 19% of national income in Europe versus 8% in the US, and indirect taxes (14% versus 7%). Meanwhile, both regions collected comparable amounts of revenue from income and wealth taxes (10-11%) and from corporate income taxes (3%). The macroeconomic tax rate was larger in Northern Europe (52%) than in Western Europe (48%) and Eastern Europe (41%), due mostly to the larger share of national income collected in income and corporate taxes. If one excludes contributory social contributions from the analysis (that is, contributions financing the pension and unemployment systems), then the gap between Europe and the US decreases but remains significant: 23% of national income was collected in non-contributory taxes in the US in 2007-2017, compared to 30% in Europe….”

The Structure and Distribution of Taxes

“…TableIVprovides a more detailed picture of the rise of pretax income inequality by showing the real average annual income growth of selected income groups in our four regions of interest over the 1980-2017 and 2007-2017 periods.30 National incomes grew at a modest yearly rate in the past four decades in Europe and the US: 1% in Western Europe, 1.2% in Eastern Europe, 1.4% in the US, and 1.8% in Northern Europe. In all regions, however, growth rates have been markedly higher the further one moves towards the top end of the distribution. The average pretax income of the top 1% thus rose at a rate of 1.9% in Western Europe, 3.2% in Northern Europe, 3.3% in the US, and 3.8% in Eastern Europe. Meanwhile, middle-income groups saw their average pretax incomes grow at a rate closer to the average of the full population in all regions. The bottom 20% benefited the least from real national income growth: their average income increased at a rate of 1.2% in Northern Europe and 0.7% in Western Europe, while it decreased at a rate of 1.3% in Eastern Europe and fell on average by 1.1% every year in the United States….”

“..The US ranks third of all the countries considered here, with an increase in the top 10% share of almost 14 percentage points. In Western Europe, Germany is the country where the top 10% share grew the most (+ 9 percentage points)…”

“…We now turn to documenting the evolution of pretax income inequality in Europe and the US. FigureIIashows the evolution of the top 10% pretax income share in the US, Eastern Europe, Western Europe, and Northern Europe from 1980 to 2017. The United States remained more unequal than most European countries throughout the entire period, but the gap between Europe and the US has widened significantly over time.27Indeed, the top 10% rose most rapidly and steadily in the US (from 34% to 48%), followed by Eastern Europe (from 24% to 36%), Western Europe (from 30% to 35%), and Northern Europe (from 26% to 31%). From 1980 to 2017, Eastern Europe shifted from being the least unequal to the most unequal European region. A significant part of this change occurred between 1989 and 1995, following thedisintegration of the Soviet Union and the transition of Eastern European countrie to market economies…”

The Distribution of Pretax Income Growth

“…How do pretax incomes vary in Europe and the United States today? Table III provides a first answer to this question by displaying the average incomes and income shares of key income groups in Western Europe, Northern Europe, Eastern Europe, and the US in 2017. The average national income per adult stood at e52,700 in the US at purchasing power parity, compared to e44,900 in Northern Europe, e35,300 in Western Europe, and e21,700 in Eastern Europe. In Europe, only Norway (e55,000) and Luxembourg (e102,000) have higher average national incomes than the US.23Things look very different at the bottom of the pretax income distribution. Thebottom 50% earned only about e12,300 in the US in 2017, compared to e21,600 inNorthern Europe and e14,600 in Western Europe. Of the twenty-seven countriesconsidered in this paper, the US thus ranks third in terms of average national incomeper adult but nineteenth when it comes to the average income of the poorest 50%.24On average, pretax income inequality at the bottom is lowest in Northern Europe(with a bottom 50% share of 24%), followed by Western Europe (21%) and EasternEurope (20%). With a bottom 50% pretax income share of only 11.7%, the US is byfar the most unequal of all countries, followed by a distant Serbia (16%) and veryfar from the values observed in the Czech Republic, Iceland, Norway, and Sweden(all above 25%).25These differences appeared even more pronounced at the verybottom of the distribution: the average income of the poorest 20% was e11,600 inNorthern Europe in 2017, more than three times larger than its counterpart in theUnited States (e3,800).The same differences are visible at the top end of the distribution: the top 1% captured 21% of total pretax income in the US in 2017, compared to 12% in Eastern Europe, 11% in Western Europe, and less than 9% in Northern Europe. In 2017, the top 0.001% average pretax income exceeded e92 million in the US, nearly ten times the value observed in Northern Europe. The European countries with lowest top 1% income shares are the Netherlands, Slovenia, Iceland, Belgium, and Finland (less than 9%), while those with highest top income concentration are Germany, the United Kingdom, Greece, and Poland (13-15%).26 In summary, while the US stands out as being richer than most European countries today, differences in average national incomes mask substantial heterogeneity. With inequality levels surpassing by far those observed in any European country, theUS displays bottom pretax average incomes that barely exceed those observed inpoorer Eastern European countries. In contrast, the lower inequality levels and higheraverage incomes observed in Northern Europe imply significantly better standardsof living for the majority of the population than in the United States….”

“..The efforts made by the Luxembourg Income Study (LIS) to harmonize existing surveys, for instance, have been extremely helpful to improve the comparability of pre-2000 inequality statistics in Europe. Yet, because of sampling issues and misreporting at the top of the income distribution, surveys can picture evolutions that are inconsistent with those suggested by tax data. In this paper, we combine for the first time all these sources in a meaningful way, using new techniques and a consistent methodology. We show that correcting for the weaknesses of existing estimates does lead to substantively different conclusions on the level and evolution of inequality in Europe, the distributive impact of taxes and transfers, and how inequality and redistribution compare across European countries….”

Core Evidence

“..the main reason for Europe’s relative resistance to the rise of inequality has little to do with the direct impact of taxes and transfers. While Western and Northern European countries redistribute a larger fraction of output than the US (about 47% of national income is taxed and redistributed in Europe versus 35% in the US), the distribution of taxes and transfers does not explain the large gap between Europe and US posttax inequality levels. Quite the contrary: after accounting for all taxes and transfers, the US appears to redistribute a greater fraction of its national income to the poorest 50% than any European country. This finding stands in sharp contrast with the widespread view that “redistribution”, not “predistribution”, explains why Europe is less unequal than the US (e.g.,OECD, 2008;2011). In other words, Europe has been much more successful than the US at ensuring that its low-income groups benefit from relatively good-paying jobs. We show that the differences between our conclusions and those of the OECD are driven by several factors, including the greater underrepresentation of top incomes in US surveys, the fact that we account for indirect taxes and in-kind transfers, which are moreprogressive in the US than in Europe overall, and the inclusion of pensions in the definition of pretax income….”

“…Between 1980 and 2017, the share of pretax income that accrued to the richest 1% Europeans rose from 8% to 11% before taxes and transfers and from 7% to 9% after taxes and transfers. In the US, the top 1% pretax income share rose from 11% to 21% over the same period, and the top 1% post tax income share from 9% to 16%....”

Steve Notes

The bottom 20% in the US earn effectively zero, suggesting they don’t have jobs vs Northern Europe,which earns 21.6 euros suggesting they have significant jobs. That seems like apples to oranges. The amount transferred to the bottom 20% in the US seems very small compared to the amount calculated in the table we made of the many experts estimating the amounts. 6k euros vs tens of thousands of dollars. Lastly, they mix retirees with the poor so straightforward comparisons are very complicated/impossible. Perhaps they break them out in the online data table.

And also

3.2 delta/36.6 (average national income per capita) = 8.7% vs the chart above, which says 4.4%. I did this for the other (three) countries and found the same result: the allocation in the table seemed to be twice the number in the chart. I only have the chart for the US and not the table. So I believe I have to double the number in the chart to produce an equivalent table. But that’s too bold a leap for me to use publicly. Perhaps I don’t understand the chart or my math is wrong. I interpret the chart to be: what percent of national income is being distributed to the bottom 50% on net (i.e. less taxes plus services). On net, the US distributes more to the poor than other countries and national income per capita is larger so dollar-wise (or euro-wise in this case) more gets distributed both percentage-wise and even more so dollar-wise. Several other things made my ears perks up: Not presenting a comparable US page is a red flag. They use Piketty and Saez data for the US. But those estimates were criticized by Auten and Splinter. Pages 67 and 68 in the appendix show the (supposedly real) growth in average income (both are inflated to 2017ppp adjusted euros). But what inflation index did they use for the US and Europe, and are those indexes similarly accurate? When you inflate/deflate over that long a time period, the indexes matter. I’m always leery of data that changes significantly in a couple years. The significant down tick in the US and uptick in Europe makes my ears perk up. Things seldom change quickly. And, as far as I know, the incomes of American lesser-skilled workers grew faster than the economy on average (so their share would be growing).

Taking France as an example. It says the difference between pre and post tax income for the bottom 50% is 4.4% of national income. 21.0 (post tax per capita income for the bottom 50%, measured in 2017 purchasing poser adjusted euros) - 17.8 (pretax income for the bottom 50%) = 3.2 delta between pre and post

They have a chart like this for each country which show the net effect (i.e., minus taxes plus services)

And also

Blanchet Comment, “The figure for net redistribution shows the aggregate amount of income that is redistributed (on net) to each group, while you are calculating the change in each group’s average income. That is where the factor 2 comes from. The bottom 50% receives 4.4% on national income on net, but since that is distributed across half of the population, the change in that group’s average is twice as large. We don't show the US in our appendix because for them we are not making our own estimates, but use the data from:https://gabriel-zucman.eu/usdina/We always use the GDP implicit price deflators as price indexes, which in principle are harmonized across countries to the same extent that GDP numbers are.”

Ed Comment: Here’s the summary:

Post tax

2017 euro

ppp

Next 30

Bottom 20

Avg income bottom 50% 2017 euros

Middle 40

avg

US

26.1

8.3

19.0

56.0 (1.0)

52.7 (1.0)

Germany

23.3

10.4

18.1

42.5 (1.32)

39.2 (1.34)

France

25.7

14.1

21.0

40.4 (1.38)

36.6 (1.44)

UK

22.4

11.4

18.0

37.2 (1.50)

34.3 (1.53)

Italy

19.0

6.3

13.9

35.1 (1.59)

29.6 (1.78)

Sweden

31.1

16.6

25.3

49.1 (1.14)

43.0 (1.23)

Finland

24.0

14.5

20.2

40.1 (1.40)

36.7 (1.44)

Denmark

30.4

16.1

24.7

50.4 (1.11)

45.7 (1.15)

I don’t fully understand the numbers and need you to look at the online database and call them. On pages 261, 276, 345 and 485 (France, Germany, Italy and Sweden) they have charts that look like this:

Ed Comment:Nowhere could I find an equivalent chart for the US except for pretax (i.e. before all their calculations)—Table III in the main report. I tried to calculate post tax US amounts myself but the I couldn’t reconcile the numbers. Perhaps they have a chart I couldn’t find. or we can find it in the online database. I fear they didn’t presenting one because the numbers aren’t as comparable as they want the reader to believe. (Post tax BTW is after subtracting taxes and adding back government services. The study says the poor in Europe are heavily taxed but receive more government services.) They do make post tax comparison in charts in the appendix see below

  • Fiscal Deficits
  • Fiscal Policy
    • Government Spending
  • Workforce
    • Inequality
    • Wages/Income

Winner Takes All? Tech Clusters, Population Centers, and the Spatial Transformation of U.S. Invention

Brad Chattergoon National Bureau of Economic Research
Date Posted:
November 12, 2021
Is Database:
Database

Tech clusters now account for 34.2% of US patents, up from 11.3% in 1975-1979. Activity has reallocated from larger population centers.

The concentration of U.S. invention in tech centers has intensified, with six tech hubs accounting for 34.2% of patents from 2015-2019, up from 11.3% in 1975-1979. This shift reflects a reallocation of patent activity away from the five largest population centers of 1980, which saw their share drop from 32.2% to 18.6%. San Francisco exemplifies this trend, growing its patent share from 4.6% to 18.4%. The rise in software patents, now comprising over half of all patents, has been pivotal, with tech centers holding 45.4% of these by 2015. While non-software patenting remains stable in many cities, the overall spatial transformation suggests a potential plateau in concentration, driven by factors like immigrant inventors and new businesses. This reallocation underscores the evolving landscape of U.S. innovation, where tech clusters increasingly dominate at the expense of traditional urban centers.

New NBER from Kerr finds innovation has become increasingly concentrated, "U.S. invention has become increasingly concentrated around major tech centers since the 1970s, with implications for how much cities across the country share in concomitant local benefits. Is invention becoming a winner-takes-all race? We explore the rising spatial concentration of patents and identify an underlying stability in their distribution. Software patents have exploded to account for about half of patents today, and these patents are highly concentrated in tech centers. Tech centers also account for a growing share of non-software patents, but the reallocation, by contrast, is entirely from the five largest population centers in 1980.Non-software patenting is stable for most cities, with anchor tenants like universities playing important roles, suggesting the growing concentration of invention may be nearing its end. Immigrant inventors and new businesses aided in the spatial transformation…Figure 1 shows annual rates of U.S. patenting for tech clusters and large population centers. Beyond these two groups, we aggregate the remaining 270 MSAs and prepare a fourth group for rural areas. The thatched portion of each series is software-related, and the solid portion is nonsoftware-related. Patents are dated by their application years, and the final period of 2015-2019 is not shown due to incomplete series with respect to patent counts given future grants will occur. The share-based metrics that we focus on for most of this paper are less sensitive to this incomplete process. The rise of the six tech centers is very stark, and Figure 2 presents these data in terms of shares. The six tech centers account for 11.3% of patents from 1975-1979, but surge to 34.2% for 2015- 2019. San Francisco’s growth is from 4.6% to 18.4%. While other groups decline in share, the magnitudes and economic importance are different. The five largest population centers show the largest drop, from 32.2% to 18.6%. By contrast, the aggregate decline for the other 270 cities, from 45.5% to 41.0%, is much less. Non-urban areas also decline from 11.0% to 6.1%....”

Winner Takes All? Tech Clusters, Population Centers, and the Spatial Transformation of U.S. Invention: Extended Excerpt Image 1

Brad Chattergoon and William Kerr, "Winner Takes All? Tech Clusters, Population Centers, and the Spatial Transformation of U.S. Invention," National Bureau Of Economic Research, November 2021, https://www.nber.org/papers/w29456

Evidence, "...Figure 1 shows annual rates of U.S. patenting for tech clusters and large population centers. Beyond these two groups, we aggregate the remaining 270 MSAs and prepare a fourth group for rural areas. The thatched portion of each series is software-related, and the solid portion is non-software-related. Patents are dated by their application years, and the final period of 2015-2019 is not shown due to incomplete series with respect to patent counts given future grants will occur. The share-based metrics that we focus on for most of this paper are less sensitive to this incomplete process. The rise of the six tech centers is very stark, and Figure 2 presents these data in terms of shares. The six tech centers account for 11.3% of patents from 1975-1979, but surge to 34.2% for 2015-2019. San Francisco’s growth is from 4.6% to 18.4%.While other groups decline in share, the magnitudes and economic importance are different. The five largest population centers show the largest drop, from 32.2% to 18.6%. By contrast, the aggregate decline for the other 270 cities, from 45.5% to 41.0%, is much less. Non-urban areas also decline from 11.0% to 6.1%. This reallocation is remarkable and has not been documented in prior work…”

Software vs Non-Software Patenting, “…Figures 1 and 2 suggest that software patenting is important for our understanding of spatial clustering and tech clusters. Software patents are a significant share of invention in all cities, but they account for well more than half of patents in tech clusters. Panel B in Figure 2 shows that the tech centers account for 45.4% of software patents after 2015, more than double their starting share of 20.2%. San Francisco again features prominently with 25.8% of software patents filed after 2015. This reallocation pulled from all regions. Panel B of Figure 2 shows that tech clusters are also important for non-software patents (solid lines), growing from 11.0% to 23.1% across the period. San Francisco is 11.1%. However, the share for the 270 MSAs grows slightly from 45.5% to 48.1%. The shift is instead from the five largest cities in 1980, which fall from 32.3% to 20.0%. These cities have remained mostly prosperous and often hold leading positions in important sectors (e.g., media in Los Angeles, finance in New York). But, while patents continue to increase in a super-linear relationship to city population, invention has become less coupled to the largest cities...”

Core findings, "... Our contribution is to quantify how much of the rise of tech centers like Boston, Seattle, and San Francisco since the 1970s is due to a shift of patenting from the biggest population centers in 1980 like NYC and LA. The magnitudes are large: the 13.6% reduction from the 1970s to 2015-2019 in the patent share accounted for by the five largest population centers in 1980 is comparable to the combined patenting of the 238 MSAs with the least patenting in 2015-2019….”

Tech Cluster definition, "...Defining a tech cluster requires consideration of complementary inputs to patenting like venture capital investment.7 We follow Kerr and Robert-Nicoud (2020) and Rosenthal and Strange (2020) by using two criteria that reflect the scale and density of local tech activity: 1) the city ranks among the top 15 cities for patents and venture capital investment (the scale of activity) and 2) the city holds shares for patents, venture capital, employment in R&D-intensive sectors, and employment in digital-connected occupations that exceed its population share (the density of activity).
Six metropolitan statistical areas (MSAs8) satisfy these scale and density criteria: San Francisco, Boston, Seattle, San Diego, Denver, and Austin. New York and Los Angeles are ambiguous, as the cities hold large scale but fall short on several density requirements...."
Large cities, "...In 1980, the ten most populated MSAs were New York City, Los Angeles, Chicago, Philadelphia, Detroit, San Francisco, Washington DC, Dallas-Ft. Worth, Houston, and Boston. San Francisco (#6) and Boston (#10) are two of the identified tech clusters, and the next largest is San Diego at #17 in terms of the 1980 population ranking. Our analysis focuses on the reallocation of patenting from the five largest MSAs in 1980 in terms of population that rank ahead of San Francisco to tech centers...."

  • Startups
  • Comparisons
    • Geography (Urban/Rural)
    • Historical
  • Productivity
    • Innovation/Research
    • Institutional Capabilities
    • Intangibles
    • Investment
    • Workforce Reorganization
      • Urban vs Rural

The Economics of Inequality in High-Wage Economies

Edward Conard Oxford University Press
Date Posted:
January 1, 2021

Inequality is mostly the result of an increasing premium on returns from risk and high-skilled labor ushered in by technological disruption and the feedback loop of elite talent working to increase their own productivity—a logical outcome when properly trained talent constrains growth.

Inequality is mostly the result of an increasing premium on returns from risk and high-skilled labor ushered in by...
The advent of information technology opened a window of investment opportunities that has exceeded the supply of properly trained talent while trade with low-wage economies, low-skilled immigration, trade deficits, and aging demographics have relieved constraints to low-skilled labor and risk-averse savings. As the economy devotes more resources to raising the productivity of talent, low-skilled productivity and wage growth have slowed. With a constrained supply of risk-reducing talent allocated to more productive endeavors, an unconstrained supply of risk-averse savings has lowered interest rates. With improbable innovation needed to capitalize on the value of information, high returns to success have fortunately motivated increased risk-taking, despite the declining productivity of innovators. Proponents of income redistribution have concluded that high returns to success and slowing productivity growth, despite low interest rates, are evidence of rising cronyism, notwithstanding extensive evidence to the contrary. This chapter provides an alternative explanation.

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The Fall of the Labor Share and the Rise of Superstar Firms

David David Autor Dorn, Lawrence Katz, Christina Patterson, John Van Reenen Quarterly Journal of Economics
Date Posted:
May 20, 2020
Is Database:
Database
Is Important:
Important

The decline in labor’s share of GDP is linked to the rise of superstar firms, which dominate industries with high markups & low labor shares.

The decline in labor’s share of GDP is linked to the rise of superstar firms, which dominate industries with high...
The decline in labor's share of GDP in the U.S. and other countries is linked to the rise of superstar firms, which dominate industries with high markups and low labor shares. Analysis of U.S. Economic Census data since 1982 shows that industry sales are increasingly concentrated in a few firms, leading to significant declines in labor share where concentration is highest. This trend is driven by reallocation rather than a decrease in the average labor share across all firms. The greatest reallocation occurs in sectors with rising market concentration, which also experience faster productivity growth. Consequently, the aggregate markup increases more than that of the typical firm. These patterns are observed not only in the U.S. but also internationally, suggesting a global shift towards market concentration and its impact on labor share.

“…The fall of labor’s share of GDP in the United States and many other countries in recent decades is well documented but its causes remain uncertain. Existing empirical assessments typically rely on industry or macro data, obscuring heterogeneity among firms. In this paper, we analyze micro panel data from the U.S. Economic Census since 1982 and document empirical patterns to assess a new interpretation of the fall in the labor share based on the rise of “superstar firms.” If globalization or technological changes push sales towards the most productive firms in each industry, product market concentration will rise as industries become increasingly dominated by superstar firms, which have high markups and a low labor share of value-added. We empirically assess seven predictions of this hypothesis: (i) industry sales will increasingly concentrate in a small number of firms; (ii) industries where concentration rises most will have the largest declines in the labor share; (iii) the fall in the labor share will be driven largely by reallocation rather than a fall in the unweighted mean labor share across all firms; (iv) the between-firm reallocation component of the fall in the labor share will be greatest in the sectors with the largest increases in market concentration; (v) the industries that are becoming more concentrated will exhibit faster growth of productivity; (vi) the aggregate markup will rise more than the typical firm’s markup; and (vii) these patterns should be observed not only in U.S. firms, but also internationally. We find support for all of these predictions…..”

David Autor, David Dorn, Lawrence Katz, Christina Patterson, John Van Reenen, “The Fall of the Labor Share and the Rise of Superstar Firms,“ Quarterly Journal Of Economics, October 2019, https://economics.mit.edu/files/12979

  • Productivity
    • Investment
    • Workforce Reorganization
      • High vs Low Skill

The Effect of High-Tech Clusters on the Productivity of Top Inventors

Enrico Moretti National Bureau of Economic Research
Date Posted:
September 5, 2019
Is Database:
Database
Is Important:
Important

High-tech clusters significantly impact inventor productivity, as evidenced by the 49.2% decline in Rochester’s high-tech cluster following Kodak’s collapse, which led to a 20.6% productivity drop for non-Kodak inventors from 1996 to 2007.

High-tech clusters significantly impact inventor productivity, as evidenced by the 49.2% decline in Rochester's high-tech cluster following Kodak's collapse, which led to a 20.6% productivity drop for non-Kodak inventors from 1996 to 2007. Conversely, Microsoft's presence in Seattle increased the productivity of non-Microsoft computer programmers by 8%. The elasticity of patent production with respect to cluster size is 0.0662, indicating that moving to a larger cluster can boost productivity by up to 12%. These findings highlight the macroeconomic benefits of clustering, as a uniform distribution of inventors across cities would reduce US patent output by 11.07%. Understanding these spillover effects can guide policy decisions on attracting high-tech firms.

new Moretti, really interesting on high tech clusters. for example impact of the demise of Kodak on the broader Rochester high-tech cluster reduce the cluster by 49.2% (data runs through 2007) and the virtuous circle that high impact firms create (Microsoft raised the productivity of non-Microsoft computer programmers in Seattle by 8%)

“… The high-tech sector is increasingly concentrated in a small number of expensive cities, with the top ten cities in “Computer Science”, “Semiconductors” and “Biology and Chemistry”, accounting for 70%, 79% and 59% of inventors, respectively…..These shares were significantly larger in 2007 than in 1971, pointing to increasing geographical agglomeration of inventors….. I use longitudinal data on top inventors based on the universe of US patents 1971 – 2007 to quantify the productivity advantages of Silicon-Valley style clusters and their implications for the overall production of patents in the US. I relate the number of patents produced by an inventor in a year to the size of the local cluster, defined as a city × research field × year. I first study the experience of Rochester NY, whose high-tech cluster declined due to the demise of its main employer, Kodak. Due to the growth of digital photography, Kodak employment collapsed after 1996, resulting in a 49.2% decline in the size of the Rochester high-tech cluster. I test whether the change in cluster size affected the productivity of inventors outside Kodak and the photography sector. I find that between 1996 and 2007 the productivity of non-Kodak inventors in Rochester declined by 20.6% relative to inventors in other cities, conditional on inventor fixed effects.In the second part of the paper, I turn to estimates based on all the data in the sample. I find that when an inventor moves to a larger cluster she experiences significant increases in the number of patents produced and the number ofcitations received. Conditional on inventor, firm, and city × year effects, the elasticity of number of patents produced with respect to cluster size is 0.0662 (0.0138).The productivity increase follows the move and there is no evidence of pre-trends. IV estimates based on the geographical structure of firms with laboratories in multiple cities are statistically similar to OLS estimates….The elasticity of number of patents in a year with respect to cluster size is 0.0662 (0.0138). The estimated elasticity implies that a computer scientist moving from the median cluster in computer science (Gainesville, FL) to the cluster at the 75th percentile of size (Richmond, VA) would experience a 12.0% increase in productivity, holding constant the inventor and the firm. In biology and chemistry, a move from the median cluster—Boise, ID—to the 75th percentile cluster—State College, PA—is associated with a productivity gain of 8.4%, holding constant the inventor and the firm…..Estimates of the elasticity of productivity with respect to cluster size can be used to quantify the spillover effects that a firm generates within a cluster. These estimates indicate that the size of the spillover varies enormously across firms. The spillover effect generated by the average firm in the average city is 0.3% and 0.24% in computer science and biology and chemistry, respectively. But it is much larger for firms that account for a large number of inventors in the local cluster. For example, the productivity of non-Microsoft computer scientist in Seattle is estimated to be 8.06% higher because of the presence of Microsoft in the local computer science cluster. This large effect reflects Microsoft remarkable size in this field in Seattle. Having estimates of the productivity spillover that a specific firm generates in a specific cluster may prove useful to local and state governments that offer subsidies to attract high-tech firms to their jurisdiction…..In the final part of the paper, I use the estimated elasticity of productivity with respect to cluster size to quantify the aggregate effects of geographical agglomeration on the overall production of patents in the US. I find macroeconomic benefits of clustering for the US as a whole. In a counterfactual scenario where the quality of U.S. inventors is held constant but their geographical location is changed so that all cities have the same number of inventors in each field, inventor productivity would increase in small clusters and decline in large clusters. On net, the overall number of patents produced in the US in a year would be 11.07% smaller….”

Enrico Moretti, “The Effect of High-Tech Clusters on the Productivity of Top Inventors,” National Bureau of Economic Research, August 2019, https://eml.berkeley.edu//~moretti/clusters.pdf

  • Productivity
    • Innovation/Research
    • Institutional Capabilities
  • Comparisons
    • Historical

The Effect of State Taxes on the Geographical Location of Top Earners: Evidence from Star Scientists

Enrico Moretti American Economic Review
Date Posted:
January 15, 2019
Is Database:
Database
Is Important:
Important

NY State cutting personal income tax rate on top 1% of earners in 2006 increased net inflow of star scientists to NYS by +3% a year.

The elasticity of mobility for star scientists in response to state tax changes is notably high, with a long-run elasticity of 1.7 for personal income taxes. This suggests that a reduction in personal income tax rates can significantly increase the inflow of top talent. For instance, New York's 2006 cut in personal income tax rate for the top 1% from 7.5% to 6.85% resulted in a net inflow increase of star scientists by 3% annually. Over a decade, this policy added 30 star scientists to New York's stock, marking a 2.6% rise. These findings highlight the substantial impact of tax policy on the geographical distribution of highly skilled workers, although other factors like innovation clusters also play a crucial role in location decisions.

We looked at a preliminary version of this paper but here is the final version. Moretti on the elasticity of mobility of human talent in the face of high tax rates. Findings should be useful.

"...We focus on the locational outcomes of star scientists, defined as scientists—in the private sector as well as academia and government—with patent counts in the top 5 percent of the distribution.....We define star inventors, in a given year, as those who are at or above the ninety-fifth percentile in number of patents over the past ten years. In other words, stars are exceptionally prolific patenters.....The state pair with the most bilateral flows over this decade was California-Texas; 26 star scientists per year moved from Texas to California and 25 per year moved from California to Texas. Close behind was California-Massachusetts, with 25 per year moving from Massachusetts to California and 24 moving in the opposite direction....We uncover large, stable, and precisely estimated effects of personal and corporate taxes on star scientists’ migration patterns. The long-run elasticity of mobility relative to taxes is 1.7 for personal income taxes, 1.8 for state corporate income tax, and 1.6 for the investment tax credit. In terms of stocks, our elasticities imply that if the net-of-tax rate increases in a state (holding other states’ rates constant), due to a cut in the personal income average tax rate or the corporate tax, the stock of scientists in the state will rise by 0.4 or 0.42 percent per year for as long as the increase in the net-of-tax rate differential lasts. These elasticities are economically large and significantly larger than the conventional labor supply elasticity. The effect on mobility is small in the short run, and tends to grow over time.While we can’t rule out that our estimates are biased by unobserved demand or supply shocks, a number of additional pieces of evidence lend credibility to a causal interpretation of our estimates. First, we find no evidence of pretrends: changes in mobility follow changes in taxes and do not to precede them. Second, the effect of corporate income taxes is concentrated among private sector inventors: no effect is found on academic and government researchers. Third, corporate taxes only matter in states where the wage bill enters the state’s formula for apportioning multistate income. No effect is found in states that apportion income based only on sales (in which case labor’s location has little or no effect on the tax bill). We also find no evidence that changes in state taxes are correlated with changes in the fortunes of local firms in the innovation sector in the years leading up to the tax change. Finally, within-firm evidence suggests that multistate firms adjust the share of employment in each state as a function of business taxes. Overall, we conclude that state taxes have significant effect on the geographical location of star scientists and possibly other highly skilled workers. While there are many other factors that drive when innovative individual and innovative companies decide to locate, there are enough firms and workers on the margin that relative taxes matter....Of course, taxes are not the only factor that can determine the location of star scientists. Indeed, we find a limited cross-sectional relationship between state taxes and number of star scientists in a state as the effect is swamped by all the other differences across states. California, for example, has relatively high taxes throughout our sample period, but it is also attractive to scientists because of the historical presence of innovation clusters like Silicon Valley and the San Diego biotech cluster....As an illustration, our estimates imply that the effect of New York cutting its statutory personal income tax rate on the top 1 percent of earners from 7.5 percent to 6.85 percent in 2006 was to increase the net inflow of star scientists to the state by about 3 per year, which is a sizable effect over time. Over a ten-year period, for instance, this implies an addition of 30 to New York’s stock of star scientists—a 2.6 percent increase...."

Enrico Moretti and Daniel Wilson, "The Effect of State Taxes on the Geographical Location of Top Earners: Evidence from Star Scientists,"American Economic Review, 2017, https://eml.berkeley.edu//~moretti/taxes.pdf

  • Productivity
    • Incentives/Risk-Taking
    • Innovation/Research
  • Comparisons
    • Geography (Urban/Rural)
    • Other Comparison
  • Fiscal Policy
    • Taxation

Europe is Pricing Itself Out of Existence

Andrew Lees Macro Strategy Partnership
Date Posted:
November 11, 2024
Is Database:
Database
Is Important:
Important

.@MacrostrategyP argues that the EU has “traded growth for ideology” with “renewable electricity price 5x that of conventional electricity.” In March 2024 German businesses’ electricity prices were 1.7x prices in the US and 2.8x in China.

All other things being equal, Europe paid 166.3% more for its primary energy mix last year than had it used conventional energy sources. It paid 2.23 percentage points more of GDP – (5.6% rather 3.37%) - on primary energy than had its fuel mix not included renewables, which largely explains why European GDP growth has been minimal. As renewable electricity grows as a percentage of the mix, its high cost has reduced energy consumption. Since peaking in 2006, primary energy consumption across the European Union has fallen by a massive 17.47%. Renewable energy has risen to 16.6% of the primary energy mix, but in doing so, with renewable electricity price 5 times that of conventional electricity, it has reduced by a similar amount the overall energy the economy has been able to afford. Whilst GDP has held up, the economy has reshaped dramatically, with for example French and German industrial production down around 14% from their respective highs, and Italian down 25%. Beyond the reshaping of the economy to less energy intensive industries, it is also likely that the decline in primary energy use has been offset by the consumption of the internal energy gradient, and the resultant aging and loss of capital stock.

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